Google Adds New Features to Cloud Trace Application Debugging Tool

Updates will improve the ability for developers to identify performance-slowing problems in their apps, the company says.

Google has updated its Cloud Trace cloud application debugging tool with new features that it says will help enterprises troubleshoot and mitigate performance issues in a more efficient manner.
The updates include an automatic performance analysis function, a latency detection capability and an optimized user interface that provides developers with a single unified view of performance-related metrics.
The new functions are based on feedback from the thousands of developers who have been testing Cloud Trace since it was released in beta form about a year ago, Sharat Shroff, product manager for Google Cloud Platform, wrote in a blog announcing the new features.
Google will introduce several more improvements in the coming weeks, including better support for Google Container Engine and Google Compute Engine, Shroff said.

Google announced plans for Cloud Trace back in mid-2014 as a way to give developers better visibility into application code running in production on Google's cloud infrastructure. It released a beta version of the technology last January.

The company has said it wants to give developers the ability to identify issues in code, down to the specific line or lines of code that may be dragging down overall performance of a running application. The tool generates reports that developers can use to diagnose problems and find the source for slow requests, Google has previously noted.
Google officially describes it as a tracing tool for collecting latency data from cloud applications running in the company's Cloud Engine infrastructure. "It helps you understand how long it takes your application to handle incoming requests from users or other applications, and how long it takes to complete operations like [Remote Procedure Calls] performed when handling the requests," the company has noted.
Google has argued that such capabilities are critical at a time when organizations are increasingly moving to micro-services architectures and application containerization.
Cloud Trace is one of three performance optimization technologies that Google offers application developers. The other two are Cloud Debugger and Cloud Monitoring. Cloud Debugger is a tool for inspecting Python and Java applications at any point in their code, while Cloud Monitoring is a performance-monitoring feature.
This week's updates build on Cloud Trace's existing capabilities, Shroff wrote. One of the updates is a new automatic tracing and performance analysis function that continuously inspects the memory cache size, cursor usage and other aspects of application requests, to identify opportunities for improving them, Shroff said. When Cloud Trace identifies a potential issue with an application request, it generates a report highlighting the problem along with recommendations for addressing it.
Another new feature in Cloud Trace is what Google described as a latency shift detection feature that allows developers to quickly identify minor as well as significant changes in application latencies.